I am using twitter API to generate sentiments. I am trying to generate a word-cloud based on tweets. Here is my code to generate a wordcloud wordcloud(clean.tweets, random.order=F,max.words=80,...

I am trying to get the score of the best match using difflib.get_close_matches: import difflib best_match = difflib.get_close_matches(str,str_list,1)[0] I know of the option to add 'cutoff' par...

If I have a text containing for example an article of a newspaper in Catalan language, how could I find all cities from that text? I have been looking at the package nltk for python and I have dow...

Hey I have a csv with multilingual text. All I want is a column appended with a the language detected. So I coded as below, from langdetect import detect import csv with open('C:\\Users\\dell\\Do...

I don't understand type conversion. I know this isn't right, all I get is a bunch of hieroglyphs. f, _ := os.Open("test.pdf") defer f.Close() io.Copy(os.Stdout, f) I want to work with the strings...

I have a classic NLP problem, I have to classify a news as fake or real. I have created two sets of features: A) Bigram Term Frequency-Inverse Document Frequency B) Approximately 20 Features ass...

Natural Language Processing (NLP), especially for English, has evolved into the stage where stemming would become an archaic technology if "perfect" lemmatizers exist. It's because stemmers change ...

I am facing the below error while working on the TM package with R. library("tm") Loading required package: NLP Warning messages: 1: package ‘tm’ was built under R version 3.4.2 2: package ‘NLP’...

I'm doing text analysis over reddit comments, and I want to calculate the TF-IDF within BigQuery.

I have a huge dataset which is similar to the columns posted below NameofEmployee <- c(x, y, z, a) Region <- c("Pune", "Orissa", "Orisa", "Poone") As you can see, in the Region colum...

I have been using JJ Allaire's guide to using word embeddings in neural network model for text processing (https://jjallaire.github.io/deep-learning-with-r-notebooks/notebooks/6.1-using-word-embedd...

I'm trying to do some text analysis to determine if a given string is... talking about politics. I'm thinking I could create a neural network where the input is either a string or a list of words (...

If I use the TfidfVectorizer from sklearn to generate feature vectors as: features = TfidfVectorizer(min_df=0.2, ngram_range=(1,3)).fit_transform(myDocuments) How would I then generate feature ve...

I'm thinking about use word n-grams techniques on a raw text. But I have a doubt: does it have sense use word n-grams after applying lemma/stemming on text? If not, why should I use word n-grams o...

I'm a new-bee to AI and want to perform the below exercise. Can you please suggest the way to achieve it using python: Scenario - I have list of businesses of some companies as below like: 1. AI...

I am using mallet topic modelling sample code and though it runs fine, I would like to know what the parameters of this statement actually mean? instances.addThruPipe(new CsvIterator(new FileReade...

I'm trying to model twitter stream data with topic models. Gensim, being an easy to use solution, is impressive in it's simplicity. It has a truly online implementation for LSI, but not for LDA. Fo...

I want to convert this matrix into a pandas dataframe. csc_matrix The first number in the bracket should be the index, the second number being columns and the number in the end being the data. I ...

Here is my code: from sklearn.svm import SVC from sklearn.grid_search import GridSearchCV from sklearn.cross_validation import KFold from sklearn.feature_extraction.text import TfidfVectorizer fro...

Here's an appeal for a better way to do something that I can already do inefficiently: filter a series of n-gram tokens using "stop words" so that the occurrence of any stop word term in an n-gram ...

I am doing some text analysis work in Python. Unfortunately, I need to switch to R in order to use a particular package (unfortunately, the package cannot be replicated in Python easily). Current...

I have been breaking my head over this one over the last few days. I searched all the SO archives and tried the suggested solutions but just can't seem to get this to work. I have sets of txt docum...

I have a PDF file with valuable textual information. The problem is that I cannot extract the text, all I get is a bunch of garbled symbols. The same happens if I copy and paste the text fro...

This is a Homework question. I have a huge document full of words. My challenge is to classify these words into different groups/clusters that adequately represent the words. My strategy to deal wi...

How do I use sklearn CountVectorizer with both 'word' and 'char' analyzer? http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html I could extract the...